This invention relates to a system and methods for optimizing the sharpening of digital images. It is a well-known problem to sharpen an image after it has been taken in order to remedy blurriness, if the image is out of focus, or to simulate a better film resolution, i.e., to create an image that looks like it was taken on a medium format camera while it was in fact taken on a small format 35 mm camera.
The problem is that in order to really make an image sharper, you would have to add details which are missing due to insufficient optical resolution or due to the blurriness resulting from a poorly configured or out-of-focus lens. This is not possible for any computer.
Hence, the most popular method that is used to sharpen images, the unsharp mask filter, does not actually make an image sharper, as will be known to those skilled in the art with reference to this disclosure. The unsharp mask method simply makes the image look sharper by making the smallest parts appear more “contrasty” or appear with more apparent clarity. It does this by in effect detecting all edges in the image and making the dark side of that edge even darker, and the light side of that edge even lighter, so that along most edges in the image some dark or light halos are created, having a halo width. The unsharp mask filter locates pixels that differ from surrounding pixels by a specified sharpening threshold, and increases the pixels' contrast by a specified sharpening strength, which is most often expressed as a percentage. The sharpening radius of the region to which each pixel is compared may also be specified, and in practice this is a critical factor in the final appearance of the image, since it determines halo width.
Since the unsharp mask filter creates the optical illusion of sharpness (instead of adding details), in many cases it also does a good job when applied to images that in fact already have sufficient resolution.
The unsharp mask filter operates in the following way, as will be known to those skilled in the art with reference to this disclosure, which in the typical user case will be performed ad hoc through an image processing program offering an unsharp mask filter, such as the image processing program sold under the trademark PHOTOSHOP®.
The user applies the unsharp mask filter by communicating with the image processing program through a dialog box, typically by entering a desired sharpening radius, sharpening strength, and sharpening threshold, while watching a preview on the screen of how the image changes. By this ad hoc procedure, the image is sharpened only in relation to the image's on-screen characteristics, and not in relation to the image as it appears after the printing process. That means that, depending on the printer, it is very likely that the image will be printed over-sharpened or under-sharpened. More advanced users try to bring their experience with the printing process into this, but it is uniformly understood that the risk of over or under sharpening still remains. Furthermore, by entering these values manually, there is no way of gaining a consistent look, and all images will look different since they are being sharpened inconsistently. This is a drawback for the visual appearance of the print, especially if several images are printed on the same page.
It is also a well-known problem that when sharpening an image using the unsharp mask method, color changes occur to the target image. When applied to an image the unsharp mask filter does not provide a method for treating colors. In addition to that, there are more problems with unsharp mask, such as that there may occur aliasing, i.e., some pixel structures may become more apparent and lead to unwanted structures (Moirée). Also, if implementing the unsharp mask algorithm based on the CMYK, RGB or Lab image modes, you will have unnatural saturations at the halos. Briefly, sharpening in RGB leads to color-irritations, while sharpening in CMYK and Lab typically leads to under saturated, weak-looking halos, which influence the overall appearance of the image negatively. A third problem is that there is currently no way of reducing noise in a way that the image still looks natural—the currently existing algorithms of reducing noise always make the image look unnatural. Another problem is that there are some regions in images, especially foliage, which are easily over-sharpened, simply because they contain more structures and hence will lead to more halos than other regions.
Prior methods for calculating parameters for use in the unsharp mask filter have focused upon sharpening strength as the key parameter. U.S. Pat. No. 5,867,606 to Tretter for “Apparatus and Method for Determining the Appropriate Amount of Sharpening for an Image” discloses a sharpening parameter selection system that determines the sharpening strength parameter. U.S. Pat. No. 4,591,923 for “Method and Apparatus for Intensifying Sharpness of Picture Images” discloses a method for determining the degree of sharpness intensification. Such methods fail to recognize, however, that the most important parameter in utilization of the unsharp mask filter is actually the sharpening radius.
The unsharp mask method therefore has these key problems: the presence of three apparently independent variables, e.g., sharpening strength, sharpening threshold, and sharpening radius, the ad hoc method of visual trial and error previewing, the assumption that sharpening strength is the key parameter in application of the unsharp mask filter, the failure to recognize that for a given image there is a preferred sharpening radius which leads to optimal results, dependent to a first approximation upon printer type, printer resolution, image pixel dimensions, and image printing size, and to a second approximation upon viewing distance and image detail, a lack of hue protection techniques for correcting color changes occurring during application of the unsharp mask filter, the presence of aliasing and unnatural saturation in sharpened images, over-sharpening of detail area, and lack of noise reduction. What is needed is a system and methods for determining the preferred sharpening radius for the unsharp mask filter for a given image, using at a minimum parameters based upon printer type, printer resolution, image pixel dimensions, and image printing size, and preferably also upon viewing distance and image detail, and which provides a method for correcting color changes occurring during sharpening, while correcting for aliasing and unnatural saturation in sharpened images, prevent over-sharpening of detail area, and effectively reduce noise.